High-throughput diagnostic markers for foliar fungal disease resistance and high oleic acid content in groundnut.

BACKGROUND: Foliar diseases namely late leaf spot (LLS) and leaf rust (LR) reduce yield and deteriorate fodder quality in groundnut. Also the high oleic acid content has emerged as one of the most important traits for industries and consumers due to its increased shelf life and health benefits. RESULTS: Genetic mapping combined with pooled sequencing approaches identified candidate resistance genes (LLSR1 and LLSR2 for LLS and LR1 for LR) for both foliar fungal diseases. The LLS-A02 locus housed LLSR1 gene for LLS resistance, while, LLS-A03 housed LLSR2 and LR1 genes for LLS and LR resistance, respectively. A total of 49 KASPs markers were developed from the genomic regions of important disease resistance genes, such as NBS-LRR, purple acid phosphatase, pentatricopeptide repeat-containing protein, and serine/threonine-protein phosphatase. Among the 49 KASP markers, 41 KASPs were validated successfully on a validation panel of contrasting germplasm and breeding lines. Of the 41 validated KASPs, 39 KASPs were designed for rust and LLS resistance, while two KASPs were developed using fatty acid desaturase (FAD) genes to control high oleic acid levels. These validated KASP markers have been extensively used by various groundnut breeding programs across the world which led to development of thousands of advanced breeding lines and few of them also released for commercial cultivation. CONCLUSION: In this study, high-throughput and cost-effective KASP assays were developed, validated and successfully deployed to improve the resistance against foliar fungal diseases and oleic acid in groundnut. So far deployment of allele-specific and KASP diagnostic markers facilitated development and release of two rust- and LLS-resistant varieties and five high-oleic acid groundnut varieties in India. These validated markers provide opportunities for routine deployment in groundnut breeding programs.

Identification of diagnostic markers related to inflammatory response and cellular senescence in endometriosis using machine learning and in vitro experiment.

OBJECTIVE: To understand the association between chronic inflammation, cellular senescence, and immunological infiltration in endometriosis. METHODS: Datasets from GEO comprising 108 endometriosis and 97 healthy human samples and the human endometrial stromal cell. Differentially expressed genes were identified using Limma and WGCNA. Inflammatory response-related subtypes were constructed using consensus clustering analysis. The CIBERSORT algorithm and correlation analyses assessed immune cell infiltration. LASSO, SVM-RFE, and RF identified diagnostic genes. Functional enrichment analysis and multifactor regulatory networks established functional effects. Nomograms, internal and external validations, and in vitro experiments validated the diagnostic genes. RESULTS: Inflammatory response subtypes were highly correlated with the immune activities of B and NK cells. Sixteen genes were associated with inflammatory response and cellular senescence and six diagnostic genes (NLK, RAD51, TIMELESS, TBX3, MET, and BTG3) were identified. The six diagnostic gene models had an area under the curve of 0.828 and their expression was significantly downregulated in endometriosis samples. Low expression of NLK and BTG3 promoted the proliferation, migration, and invasion of endometriotic cells. CONCLUSIONS: Inflammatory response subtypes were successfully constructed for endometriosis. Six diagnostic genes related to inflammatory response and cellular senescence were identified and validated. Our study provides novel insights for inflammatory response in endometriosis and markers for endometriosis diagnosis and treatment.

Identification of ion channel-related genes as diagnostic markers and potential therapeutic targets for osteoarthritis through bioinformatics and machine learning-based approaches.

BACKGROUND: Osteoarthritis (OA) is a debilitating joint disorder characterized by the progressive degeneration of articular cartilage. Although the role of ion channels in OA pathogenesis is increasingly recognized, diagnostic markers and targeted therapies remain limited. METHODS: In this study, we analyzed the GSE48556 dataset to identify differentially expressed ion channel-related genes (DEGs) in OA and normal controls. We employed machine learning algorithms, least absolute shrinkage and selection operator(LASSO), and support vector machine recursive feature elimination(SVM-RFE) to select potential diagnostic markers. Then the gene set enrichment analysis (GSEA) and gene set variation analysis (GSVA) were performed to explore the potential diagnostic markers' involvement in biological pathways. Finally, weighted gene co-expression network analysis (WGCNA) was used to identify key genes associated with OA. RESULTS: We identified a total of 47 DEGs, with the majority involved in transient receptor potential (TRP) pathways. Seven genes (CHRNA4, GABRE, HTR3B, KCNG2, KCNJ2, LRRC8C, and TRPM5) were identified as the best characteristic genes for distinguishing OA from healthy samples. We performed clustering analysis and identified two distinct subtypes of OA, C1, and C2, with differential gene expression and immune cell infiltration profiles. Then we identified three key genes (PPP1R3D, ZNF101, and LOC651309) associated with OA. We constructed a prediction model using these genes and validated it using the GSE46750 dataset, demonstrating reasonable accuracy and specificity. CONCLUSIONS: Our findings provide novel insights into the role of ion channel-related genes in OA pathogenesis and offer potential diagnostic markers and therapeutic targets for the treatment of OA.

As society ages, the incidence of knee osteoarthritis continues to rise, bringing with it a series of social impacts and medical pressure. Despite the increasing recognition of the role of ion channels in the pathogenesis of OA, diagnostic markers and targeted therapies remain limited.This study investigated the role of TRP as possible diagnostic tools for OA.Seven TRP-related genes were identified as the best traits to distinguish OA from healthy samples, and then we constructed and validated risk scores for three key genes (PPP1R3D, ZNF101, and LOC651309) relevant to OA ion channel gene modules.Our findings provide novel insights into the role of ion channel-related genes in OA pathogenesis and offer a reference for further clinical diagnosis.

Dysregulation of exosomal miRNAs and their related genes in head and neck cancer patients.

Aim: The present study aimed to figure out the potential role of exosomal microRNAs, and their targeted genes in HNC detection/diagnosis. Methods: In the present study, exosomes were extracted from the serum samples of 400 HNC patients and 400 healthy controls. Exosomes were characterized using TEM, NTA, TEM-immunogold labeling and ELISA. Quantitative PCR was used to measure the expression level of exosomal miRNA-19a, miRNA-19b and targeted genes SMAD2 and SMAD4 in HNC patients and controls. Results: The deregulation of miR-19a (p < 0.01), miR-19b (p < 0.03), SMAD2 (p < 0.04) and SMAD4 (p < 0.04) was observed in HNC patients vs controls. Conclusion: ROC curve and Kaplan-Meier analysis showed the good diagnostic/prognostic value of selected exosomal microRNAs and related genes in HNC patients.

[Box: see text].

Insight into the role of mitochondrion-related gene anchor signature in mitochondrial dysfunction of neutrophilic asthma.

OBJECTIVE: At present, targeting molecular-pharmacological therapy is still difficult in neutrophilic asthma. The investigation aims to identify and validate mitochondrion-related gene signatures for diagnosis and specific targeting therapeutics in neutrophilic asthma. METHODS: Bronchial biopsy samples of neutrophilic asthma and healthy people were identified from the GSE143303 dataset and then matched with human mitochondrial gene data to obtain mitochondria-related differential genes (MitoDEGs). Signature mitochondria-related diagnostic markers were jointly screened by support vector machine (SVM) analysis, least absolute shrinkage, and selection operator (LASSO) regression. The expression of marker MitoDEGs was evaluated by validation datasets GSE147878 and GSE43696. The diagnostic value was evaluated by receiver operating characteristic (ROC) curve analysis. Meanwhile, the infiltrating immune cells were analyzed by the CIBERSORT. Finally, oxidative stress level and mitochondrial functional morphology for asthmatic mice and BEAS-2B cells were evaluated. The expression of signature MitoDEGs was verified by qPCR. RESULTS: 67 MitoDEGs were identified. Five signature MitoDEGs (SOD2, MTHFD2, PPTC7, NME6, and SLC25A18) were further screened out. The area under the curve (AUC) of signature MitoDEGs presented a good diagnostic performance (more than 0.9). There were significant differences in the expression of signature MitoDEGs between neutrophilic asthma and non-neutrophilic asthma. In addition, the basic features of mitochondrial dysfunction were demonstrated by in vitro and in vivo experiments. The expression of signature MitoDEGs in the neutrophilic asthma mice presented a significant difference from the control group. CONCLUSIONS: These MitoDEGs signatures in neutrophilic asthma may hold potential as anchor diagnostic and therapeutic targets in neutrophilic asthma.

The Association Between Thymidylate Synthase Gene Polymorphisms and the Risk of Ischemic Stroke in Chinese Han Population.

Family history of hypertension, smoking, diabetes and alcohol consumption and atherosclerotic plaque were identified as common risk factors in IS. We aimed at investigating the relationship between Thymidylate Synthase (TS) gene polymorphisms and ischemic stroke (IS).This case-control research selected and genotyped three single nucleotide polymorphisms (SNPs)of TS( rs699517, rs2790, and rs151264360) with Sanger sequencing in Chinese Han population. We also adopted logistic regression analysis in genetic models for calculating odds ratios and 95% confidence intervals. Genotype-Tissue Expression(GTEx) database analyzed the tissue-specific expression and TS polymorphisms. The ischemic stroke patients showed higher low-density lipoprotein cholesterol and total homocysteine (tHcy). It was found that patients with the TT genotype of rs699517 and GG genotype of rs2790 had larger degrees of tHcy than those with CC + CT genotypes and AA + AG genotypes, respectively. The genotype distribution of the three SNPs did not deviate from Hardy-Weinberg equilibrium (HWE). Haplotype analysis showed that T-G-del was the major haplotype in IS, and C-A-ins was the major haplotype in controls. GTEx database indicated that the rs699517 and rs2790 increased the expression of TS in healthy human and associated with TS expression level in a single tissue. In conclusion: This study has shown that TS rs699517 and rs2790 were significantly related to ischemic stroke patients.

Identification of MAD2L1 and BUB1B as Potential Biomarkers Associated with Progression and Prognosis of Ovarian Cancer.

Ovarian cancer develops insidiously and is frequently diagnosed at advanced stages. Screening for ovarian cancer is an effective strategy for reducing mortality. This study aimed to investigate the molecular mechanisms underlying the development of ovarian cancer and identify novel tumor biomarkers for the diagnosis and prognosis of ovarian cancer. Three databases containing gene expression profiles specific to serous ovarian cancer (GSE18520, GSE12470, and GSE26712) were acquired. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes were analyzed for the differentially expressed gene (DEGs). The protein-protein interaction (PPI) network was constructed using the STRING database. The pivotal genes in the PPI network were screened using the Cytoscape software. Survival curve analysis was performed using a Kaplan-Meier Plotter. The cancer genome atlas and Gene Expression Omnibus databases were used to find the relationship between Hub gene and serous ovarian cancer. PCR and immunohistochemistry were used to detect the expression of Hub gene in serous ovarian cancer tissues and cells. Downstream pathways of the candidate tumor marker genes were predicted using Gene Set Enrichment Analysis. In this study, 252 DEGs were screened for pathway enrichment. 20 Hub genes were identified. Survival analysis suggested that Aurka, Bub1b, Cenpf, Cks1b, Kif20a, Mad2l1, Racgap1, and Ube2c were associated with the survival of patients with serous ovarian cancer. MAD2L1 and BUB1B levels were significantly different in serous ovarian cancer at different stages. Finally, Mad2l1 was found to play a role in the cell cycle, oocyte meiosis, and ubiquitin-mediated proteolysis. Meanwhile, Bub1b may play a role in the cell cycle, ubiquitin-mediated proteolysis, and spliceosome processes. Mad2l1 and Bub1b could be used as markers to predict ovarian carcinogenesis and prognosis, providing candidate targets for the diagnosis and treatment of serous ovarian cancer.

The roles of chromatin regulatory factors in endometriosis.

PURPOSE: Endometriosis is an estrogen-dependent inflammatory disease and one of the most common gynecological diseases in women of reproductive age. The aim of the review was to explore the relationship between the chromatin regulatory factors and endometriosis. METHODS: By searching for literature on chromatin regulators and endometriosis in PuMed. Finally, 98 documents were selected. RESULTS: Chromatin regulators (CRs) are essential epigenetic regulatory factors that can regulate chromatin structure changes and are usually divided into three categories: DNA methylation compounds, histone modification compounds, and chromatin remodeling complexes. Noncoding RNAs are also chromatin regulators and can form heterochromatin by binding to protein complexes. Chromatin regulators cause abnormal gene expression by regulating chromatin structure, thereby affecting the occurrence and development of endometriosis. CONCLUSION: This review summarizes the participation of chromatin regulators in the mechanisms of endometriosis, and these changes in related chromatin regulators provide a comprehensive reference for diagnosis and treatment of endometriosis.

MicroRNAs: Small molecules with big impacts in liver injury.

A type of small noncoding RNAs known as microRNAs (miRNAs) fine-tune gene expression posttranscriptionally by binding to certain messenger RNA targets. Numerous physiological processes in the liver, such as differentiation, proliferation, and apoptosis, are regulated by miRNAs. Additionally, there is growing evidence that miRNAs contribute to liver pathology. Extracellular vesicles like exosomes, which contain secreted miRNAs, may facilitate paracrine and endocrine communication between various tissues by changing the gene expression and function of distal cells. The use of stable miRNAs as noninvasive biomarkers was made possible by the discovery of these molecules in body fluids. Circulating miRNAs reflect the conditions of the liver that are abnormal and may serve as new biomarkers for the early detection, prognosis, and evaluation of liver pathological states. miRNAs are appealing therapeutic targets for a range of liver disease states because altered miRNA expression is associated with deregulation of the liver's metabolism, liver damage, liver fibrosis, and tumor formation. This review provides a comprehensive review and update on miRNAs biogenesis pathways and mechanisms of miRNA-mediated gene silencing. It also outlines how miRNAs affect hepatic cell proliferation, death, and regeneration as well as hepatic detoxification. Additionally, it highlights the diverse functions that miRNAs play in the onset and progression of various liver diseases, including nonalcoholic fatty liver disease, alcoholic liver disease, fibrosis, hepatitis C virus infection, and hepatocellular carcinoma. Further, it summarizes the diverse liver-specific miRNAs, illustrating the potential merits and possible caveats of their utilization as noninvasive biomarkers and appealing therapeutic targets for liver illnesses.

Spatial Transcriptomics Reveal Pitfalls and Opportunities for the Detection of Rare High-Plasticity Breast Cancer Subtypes.

Breast cancer is one of the most prominent types of cancers, in which therapeutic resistance is a major clinical concern. Specific subtypes, such as claudin-low and metaplastic breast carcinoma (MpBC), have been associated with high nongenetic plasticity, which can facilitate resistance. The similarities and differences between these orthogonal subtypes, identified by molecular and histopathological analyses, respectively, remain insufficiently characterized. Furthermore, adequate methods to identify high-plasticity tumors to better anticipate resistance are lacking. Here, we analyzed 11 triple-negative breast tumors, including 3 claudin-low and 4 MpBC, via high-resolution spatial transcriptomics. We combined pathological annotations and deconvolution approaches to precisely identify tumor spots, on which we performed signature enrichment, differential expression, and copy number analyses. We used The Cancer Genome Atlas and Cancer Cell Line Encyclopedia public databases for external validation of expression markers. By focusing our spatial transcriptomic analyses on tumor cells in MpBC samples, we bypassed the negative impact of stromal contamination and identified specific markers that are neither expressed in other breast cancer subtypes nor expressed in stromal cells. Three markers (BMPER, POPDC3, and SH3RF3) were validated in external expression databases encompassing bulk tumor material and stroma-free cell lines. We unveiled that existing bulk expression signatures of high-plasticity breast cancers are relevant in mesenchymal transdifferentiated compartments but can be hindered by abundant stromal cells in tumor samples, negatively impacting their clinical applicability. Spatial transcriptomic analyses constitute powerful tools to identify specific expression markers and could thus enhance diagnosis and clinical care of rare high-plasticity breast cancers.

Recent Developments in Diagnostic and Prognostic Biomarkers for Colorectal Cancer: A Narrative Review.

BACKGROUND: Colorectal cancer was reported as the second most common cause of cancer death worldwide, in the year 2020. This disease is an important public health problem considering its high incidence and mortality rates. SUMMARY: The molecular events that lead to colorectal cancer include genetic and epigenetic abnormalities. Some of the most important molecular mechanisms involved include the APC/ß-catenin pathway, the microsatellite pathway, and the CpG island hypermethylation. Evidence in the literature supports a role for the microbiota in the development of colon carcinogenesis, and specific microbes may contribute to or prevent carcinogenesis. Progress in prevention, screening, and management has improved the overall prognosis of the disease when diagnosed at an early stage; yet metastatic disease continues to have a poor long-term prognosis due to late-stage diagnosis and treatment failure. Biomarkers are a key tool for early detection and prognosis and aim to reduce morbidity and mortality associated with colorectal cancer. The main focus of this narrative review is to provide an update on the recent development of diagnostic and prognostic biomarkers in stool, blood, and tumor tissue samples. KEY MESSAGES: The review focuses on recent investigations in microRNAs, cadherins, Piwi-interacting RNAs, circulating cell-free DNA, and microbiome biomarkers which can be applied for the diagnosis and prognosis of colorectal cancer.

Advances in the study of exosome-derived miRNAs in the pathogenesis, diagnosis, and treatment of systemic lupus erythematosus.

Systemic lupus erythematosus (SLE) is an inflammatory disease caused by autoantibodies, with high morbidity and mortality. It involves multiple systems, particularly the renal, which can lead to lupus nephritis (LN); its multi-system effects have a significant impact on the physical and mental health of patients. Exosomes are vesicles that are secreted during cell activity and carry a variety of nucleic acids, proteins, and lipids. They are distributed through body fluids for cellular communication. MicroRNAs (miRNAs) are nucleic acids that are packaged within the exosome that are taken up and released in response to changes in plasma membrane structure. MiRNAs are potential participants in immune and inflammatory responses, which are transported to target cells and can inhibit gene expression in receptor cells. It has been suggested that exosomal miRNA can regulate the pathogenesis of SLE and, as such, they are of value in diagnosis and treatment. In this paper, we focus on the research progress into exosomal miRNA in SLE and inspire new directions for SLE related research.

The Function and Therapeutic Potential of Circular RNA in Cardiovascular Diseases.

Circular RNA (circRNA) has a closed-loop structure, and its 3' and 5' ends are directly covalently connected by reverse splicing, which is more stable than linear RNA. CircRNAs usually possess microRNA (miRNA) binding sites, which can bind miRNAs and inhibit miRNA function. Many studies have shown that circRNAs are involved in the processes of cell senescence, proliferation and apoptosis and a series of signalling pathways, playing an important role in the prevention and treatment of diseases. CircRNAs are potential biological diagnostic markers and therapeutic targets for cardiovascular diseases (CVDs). To identify biomarkers and potential effective therapeutic targets without toxicity for heart disease, we summarize the biogenesis, biology, characterization and functions of circRNAs in CVDs, hoping that this information will shed new light on the prevention and treatment of CVDs.

DNA Markers, Pathogenicity Test, and Multilocus Sequence Analysis to Differentiate and Characterize Cereal-Specific Xanthomonas translucens Strains.

Xanthomonas translucens contains a group of bacterial pathogens that are closely related and have been divided into several pathovars based on their host range. X. translucens pv. undulosa (Xtu) and X. translucens pv. translucens (Xtt) are two important pathovars that cause bacterial leaf streak disease on wheat and barley, respectively. In this study, DNA markers were developed to differentiate Xtu and Xtt and were then used to characterize a collection of X. translucens strains with diverse origins, followed by confirmation and characterization with pathogenicity tests and multilocus sequence analysis/typing (MLSA/MLST). We first developed cleaved amplified polymorphic sequence markers based on the single-nucleotide polymorphisms within a cereal pathovar-specific DNA sequence. In addition, two Xtt-specific markers, designated Xtt-XopM and Xtt-SP1, were developed from comparative genomics among the sequenced Xtt/Xtu genomes. Using the developed markers, a collection of X. translucens strains were successfully identified as Xtu or Xtt. Pathogenicity tests on wheat and barley plants and MLSA of four housekeeping genes validated the pathovar assignation of those strains. Furthermore, MLSA revealed distinct subclades within both Xtu and Xtt groups. Seven and three sequence types were identified from MLST for Xtu and Xtt strains, respectively. The establishment of efficient Xtt/Xtu differentiation methods and characterization of those strains will be useful in studying disease epidemiology and host-pathogen interactions and breeding programs when screening for sources of resistance for these two important bacterial pathogens.

Identification of novel characteristic biomarkers and immune infiltration profile for the anaplastic thyroid cancer via machine learning algorithms.

PURPOSE: Anaplastic thyroid cancer (ATC) is a rare and lethal malignant cancer. In recent years, the application of molecular-driven targeted therapy and immunotherapy has markedly improved the prognosis of ATC. This study aimed to identify characteristic genes for ATC diagnosis and revealed the role of ATC characteristic genes in drug sensitivity and immune cell infiltration. METHODS: We downloaded ATC RNA-sequencing data from the GEO database. Following the combination and normalization of the dataset, we first divided the combined datasets into the training cohort and the validation cohort. We identified differentially expressed genes (DEGs) in ATC by differential expression analysis in the training cohort. We used two machine learning algorithms, least absolute shrinkage and selection operator (LASSO) and support vector machine-recursive feature elimination (SVM-RFE) to identify ATC characteristic genes. The CIBERSORT algorithm was performed to calculate the abundance of various immune cells in ATC. Finally, we validated the expression of ATC characteristic genes by quantitative RT-PCR (RT-qPCR) in ATC cell lines and immunohistochemistry (IHC). RESULTS: A total of 425 DEGs were identified in the training cohort, including 240 upregulated genes and 185 downregulated genes. Four ATC characteristic genes (ADM, PXDN, MMP1, and TFF3) were identified, and their diagnostic value was validated in the validation cohort (AUC in ROC analysis > 0.75). We established a practical gene expression-based nomogram to accurately predict the probability of ATC. We also found that ATC characteristic biomarkers are associated with the tumor immune microenvironment and drug sensitivity. CONCLUSION: ADM, PXDN, MMP1, and TFF3 might serve as potential ATC diagnostic biomarkers and may be helpful for ATC molecular targeted therapy and immunotherapy.

Evaluation of new biomarkers in stage III and IV endometriosis.

OBJECTIVE: To investigate the efficacy of new endometriosis biomarkers in diagnosis and treatment. METHODS: Thirty women with Stage III-IV endometriosis who were given an indication for surgery and 49 control patients were compared. Preoperative and postoperative serum levels of Annexin A5 (ANXA5), soluble intercellular adhesion molecule-1 (sICAM-1), interleukin-6 (IL-6), tumor necrosis factor-α (TNF-α), soluble vascular cell adhesion molecule-1 (sVCAM-1), vascular endothelial growth factors (VEGF) and Ca-125 measurements were compared. RESULTS: AUCs of ANXA5, sICAM-1, IL-6, TNF-α, VCAM-1, VEGF biomarkers were not found to be significant in diagnosing endometriosis when evaluated alone (p > 0.05). Only the AUC of the Ca-125 biomarker values were found to be significant with 73% sensitivity and 98% specificity (p < 0.001). However, when Ca-125 and ANXA5 were evaluated together, it was concluded that the diagnosis of endometriosis could be made with 73% sensitivity and 100% specificity. CONCLUSION: When Ca-125 and ANXA5 are evaluated together, it seems to be more valuable than Ca-125 alone in diagnosing endometriosis.

Construction of a diagnostic classifier for cervical intraepithelial neoplasia and cervical cancer based on XGBoost feature selection and random forest model.

BACKGROUND: The pathological phenotype of early-stage cervical cancer (CC) is similar to that of cervical intraepithelial neoplasia (CIN), which provides a challenge for the diagnosis of cervical precancerous lesions. Meanwhile, the existing diagnostic methods have certain subjectivity and limitations, resulting in the possibility of misdiagnosis or missed diagnosis. Hence, some methods are needed to assist diagnosis of CC and CIN. METHODS: Based on the data of CIN and CC in gene expression omnibus (GEO) dataset, the eXtreme Gradient Boosting (XGBoost) algorithm was used to screen the feature genes between CIN and CC for constructing the classifier. Incremental feature selection (IFS) curve was also used for screening. The classifier was validated for reliability using principal component analysis (PCA) dimensionality reduction analysis and heat map analysis of gene expression. Then, differentially expressed genes of CIN and CC were intersected with the classifier genes. Genes in the intersection were used as seeds for protein-protein interaction network construction and restart random walk analysis. And the genes with the top 50 affinity coefficients were selected for gene ontology (GO) and kyoto encyclopedia of genes and genome (KEGG) enrichment analyses to observe the biological functions with differences between CIN and CC. RESULTS: The peripheral blood genes of CIN and CC were analyzed, and seven genes were screened. Using this gene for classifier construction, IFS curve screening revealed that the three-feature gene classifier constructed according to the random forest model had the best effect. The results of PCA dimensionality reduction analysis and gene expression heat map analysis showed that the three-gene classifier could effectively distinguish CIN from CC. CONCLUSION: A three-gene diagnostic classifier can effectively distinguish CIN patients from CC patients and provide a reference for the clinical diagnosis of early CC.

D-Dimer, Erythrocyte Sedimentation Rate, and C-Reactive Protein Sensitivities for Periprosthetic Joint Infection Diagnosis.

BACKGROUND: There is contradicting evidence on the diagnostic value of inflammatory biomarkers for periprosthetic joint infection (PJI). We sought to quantify the sensitivity of D-dimer for acute and chronic PJI diagnosis and evaluate D-dimer lab values in the 90-day postoperative window in a control cohort of primary joint arthroplasty patients for comparison. METHODS: An institutional database was queried for patients undergoing revision procedures for PJI after total hip arthroplasty (THA) and total knee arthroplasty (TKA) from 2014 to present. CRP, ESR, and D-dimer were collected within 90 days pre and postoperatively and sensitivities for the diagnosis of PJI were calculated. The control group included patients who underwent a negative diagnostic workup for deep venous thrombosis (DVT) or pulmonary embolus (PE) and had a D-dimer lab collected within 90 days postoperatively from primary total joint arthroplasty (TJA). RESULTS: A total of 604 PJI patients were identified, and 81 patients had D-dimer, ESR, and CRP collected. There were 50/81 acute PJI patients and 31/81 chronic PJI patients who had median D-dimer values of 2,136.5 ng/mL [interquartile range (IQR): 1,642-3,966.5] and 3,336 ng/mL [IQR: 1,976-5,594]. Only the chronic PJI group had significantly higher D-dimer values when compared to the control cohort (P = .009). The sensitivity of D-dimer was calculated to be 92% and 93.5% in the acute and chronic PJI groups, respectively. CONCLUSION: Serum D-dimer may not have high diagnostic utility for acute PJI, especially in the setting of recent surgery; however, it still may be useful for patients who have chronic PJI.

Plasma Lipids Profile in the Prediction of Non-Alcoholic Steatohepatitis in Adults: A Case-Control Study.

Patients with non-alcoholic steatohepatitis (NASH) show significantly faster progress in the stages of fibrosis compared to those with non-alcoholic fatty liver (NAFL) disease. The non-invasive diagnosis of NASH remains an unmet clinical need. Preliminary data have shown that sphingolipids, especially ceramides, fatty acids, and other lipid classes may be related to the presence of NASH and the histological activity of the disease. The aim of our study was to assess the association of certain plasma lipid classes, such as fatty acids, acylcarnitines, and ceramides, with the histopathological findings in patients with NASH. The study included three groups: patients with NASH (N = 12), NAFL (N = 10), and healthy [non non-alcoholic fatty liver disease (NAFLD)] controls (N = 15). Plasma samples were collected after 12 h of fasting, and targeted analyses for fatty acids, acylcarnitines, and ceramides were performed. Baseline clinical and demographic characteristics were collected. There was no significant difference in baseline characteristics across the three groups or between NAFL and NASH patients. Patients with NASH had increased levels of several fatty acids, including, among others, fatty acid (FA) 14:0, FA 15:0, FA 18:0, FA 18:3n3, as well as Cer(d18:1/16:0), compared to NAFL patients and healthy controls. No significant difference was found between NAFL patients and healthy controls. In conclusion, patients with NASH exhibited a distinctive plasma lipid profile that can differentiate them from NAFL patients and non-NAFLD populations. More data from larger cohorts are needed to validate these findings and examine possible implications for diagnostic and management strategies of the disease.

Molecular mechanism and diagnostic marker investigation of endoplasmic reticulum stress on periodontitis.

PURPOSE: The aim of this study was to reveal the biological function of endoplasmic reticulum stress (ERS)-related genes (ERSGs) in periodontitis, and provide potential ERS diagnostic markers for clinical therapy of periodontitis. METHODS: The differentially expressed ERSGs (DE-ERSGs) were reveled based on periodontitis-related microarray dataset in Gene Expression Omnibus (GEO) database and 295 ERS in previous study, followed by a protein-protein interaction network construction. Then, the subtypes of periodontitis were explored, followed by validation with immune cell infiltration and gene set enrichment. Two machine learning algorithms were used to reveal potential ERS diagnostic markers of periodontitis. The diagnostic effect, target drug and immune correlation of these markers were further evaluated. Finally, a microRNA(miRNA)-gene interaction network was constructed. RESULTS: A total of 34 DE-ERSGs were revealed between periodontitis samples and control, followed by two subtypes investigated. There was a significant difference of ERS score, immune infiltration and Hallmark enrichment between two subtypes. Then, totally 7 ERS diagnostic markers including FCGR2B, XBP1, EDEM2, ATP2A3, ERLEC1, HYOU1 and YOD1 were explored, and the v the time-dependent ROC analysis showed a reliable result. In addition, a drug-gene network was constructed with 4 up-regulated ERS diagnostic markers and 24 drugs. Finally, based on 32 interactions, 5 diagnostic markers and 20 miRNAs, a miRNA-target network was constructed. CONCLUSIONS: Up-regulated miR-671-5p might take part in the progression of periodontitis via stimulating the expression of ATP2A3. ERSGs including XBP1 and FCGR2B might be novel diagnostic marker for periodontitis.